Hi Flink Devs, I am Srini, I work for stream processing team at LinkedIn. LinkedIn is taking a big bet on Apache Flink and migrating all the existing streaming SQL apps to Flink. You might have seen mails from some of our team members past few months. Thanks a lot for your support!
I just wanted to Say Hi to everyone before I take up some of the starter Jiras and start contributing. Thanks Again! Looking forward to collaboration :) Here are some of the quick notes about our Flink scenarios. 1. We will be using Flink SQL just for stream processing applications. 2. Most of our current SQL apps are stateless, But stateful SQL capabilities is one of the reasons we are migrating to Flink. SQL state management is an area of interest. 3. We also have customers asking for batch and streaming convergence, So SQL based batch <-> streaming convergence or engine portability of SQL apps is an area of interest. 4. We are initially on prem. But LinkedIn as a whole is betting on Cloud. So taking advantage some of the cloud capabilities like Storage compute disaggregation, Elastic compute (for auto-scaling) for Flink would be interesting. 5. We also provide a managed streaming SQL service i.e. We manage the SQL jobs for our developers. So reliability, operability and quick recovery is critical as well :). Thanks, Srini.
